Fig 1 - uploaded by Mehmet yamaç
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The image of Lena and its proxy Ψ T y obtained from CSMs, where y results from projecting the original image on a Gaussian random measurement matrix.
Source publication
Compressive Sensing (CS) theory asserts that sparse signal reconstruction is possible from a small number of linear measurements. Although CS enables low-cost linear sampling, it requires non-linear and costly reconstruction. Recent literature works show that compressive image classification is possible in CS domain without reconstruction of the si...
Contexts in source publication
Context 1
... acquisition of the proxy signal is obviously done as, ˜ S = Ψ T y, where Ψ T ∈ R N ×m is the transpose of the measurement matrix Ψ. An example proxy image is shown in Figure 1. ...
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